文章专利统计

yaked19

377人浏览 · 2025-11-02 19:07:30

yaked19 · 2025-11-02 19:07:30 发布

研究方向：
三维视觉、机器人 AI
教育背景
⚫ 2013.09 – 2016.07 广东工业大学，硕士
⚫ 2009.09 – 2013.07 华中科技大学文华学院，学士

姓名		证件类型	身份证	民族	汉
身份证(外籍填写护照)号码		职称
性别	男	职务	无	博士后（出站/在站/否）	否
出生日期	1991年10月	办公电话		是否博导	否
学位	硕士	所在单位		是否在读硕/博研究生	否
email		现从事专业	计算机视觉开发	移动电话
学历	硕士研究生	获得最终学位院校	广东工业大学	最高学位授予国别或地区	中国

一、文章

[1] C. Chen, L. Chen, X. Zhou and W. Yan, "Controlling a robot using leap motion," 2017 2nd International Conference on Robotics and Automation Engineering (ICRAE), Shanghai, China, 2017, pp. 48-51, doi: 10.1109/ICRAE.2017.8291351.

[2] 鄢武,唐观荣,苏泽荣,蔡奕松,文享龙.基于三维视觉的随机工件识别与姿态估计[J].科技视界,2019(19):66+6.

[3] Yan W, Xu Z, Zhou X, et al. Fast Object Pose Estimation Using Adaptive Threshold for Bin-Picking[J]. IEEE Access, 2020, 8: 63055-63064.

[4] Yan W, Xu C, Wu H, et al. Real Time Volume Measurement of Logistics Cartons Through 3D Point Cloud Segmentation[C]//Intelligent Robotics and Applications: 14th International Conference, ICIRA 2021, Yantai, China, October 22–25, 2021, Proceedings, Part III. 2021: 324-335.

[5] 蔡奕松,鄢武,孙克争,等.基于3D虚拟引擎的无线数据触觉手套系统[J].自动化与信息工程,2021,42(02):31-33.

[6] Yan W, Liu D, Zhai X, et al. Sample Augmentation and Orientation-aware Deep Neural Network for Logistics Objects Detection[C]//2023 IEEE 18th Conference on Industrial Electronics and Applications (ICIEA). IEEE, 2023: 948-953.

[7] Wu H, Yan W, Xu Z, et al. A framework of improving human demonstration efficiency for goal-directed robot skill learning[J]. IEEE Transactions on Cognitive and Developmental Systems, 2021, 14(4): 1743-1754.

[8] Wu H, Yan W, Xu Z, et al. A framework of robot skill learning from complex and long-horizon tasks[J]. IEEE Transactions on Automation Science and Engineering, 2021, 19(4): 3628-3638.

[9] Wu H, Yan W, Xu Z, et al. Learning robot anomaly recovery skills from multiple time-driven demonstrations[J]. Neurocomputing, 2021, 464: 522-532.

[10] Liao Z, Xu Z, Wang Q, Yan W, et al. Integrated robotic measurement and machining technology for large castings[C]//International Conference on Mechanical Engineering, Measurement Control, and Instrumentation. SPIE, 2021, 11930: 599-607.

[11] Yang L, Yan W, Xu Z, et al. Robot multimodal anomaly diagnosis by learning time-lagged complex dynamics[C]//2021 IEEE International Conference on Real-time Computing and Robotics (RCAR). IEEE, 2021: 509-514.

[12] Yang L, Yan W, Wu H. Comparison of deep learning-based methods in multimodal anomaly detection: A case study in human–robot collaboration[J]. Science Progress, 2021, 104(2): 00368504211021192.

[13] Wu H, Xu Z, Yan W, et al. Incremental learning introspective movement primitives from multimodal unstructured demonstrations[J]. IEEE Access, 2019, 7: 159022-159036.

[14] Xu Z, Li S, Zhou X, Yan W, et al. Dynamic neural networks based kinematic control for redundant manipulators with model uncertainties[J]. Neurocomputing, 2019, 329: 255-266.

[15]